Large-scale Point Cloud Registration Based on Graph Matching Optimization

Point Clouds Registration is a fundamental and challenging problem in 3D computer vision. It has been shown that the isometric transformation is an essential property in rigid point cloud registration, but the existing methods only utilize it in the outlier rejection stage. In this paper, we emphasize that the isometric transformation is also important in the feature learning stage for improving registration quality. We propose a \underline{G}raph \underline{M}atching \underline{O}ptimization based \underline{Net}work (denoted as GMONet for short), which utilizes the graph matching method to explicitly exert the isometry preserving constraints in the point feature learning stage to improve %refine the point representation. Specifically, we %use exploit the partial graph matching constraint to enhance the overlap region detection abilities of super points ($i.e.,$ down-sampled key points) and full graph matching to refine the registration accuracy at the fine-level overlap region. Meanwhile, we leverage the mini-batch sampling to improve the efficiency of the full graph matching optimization. Given high discriminative point features in the evaluation stage, we utilize the RANSAC approach to estimate the transformation between the scanned pairs. The proposed method has been evaluated on the 3DMatch/3DLoMatch benchmarks and the KITTI benchmark. The experimental results show that our method achieves competitive performance compared with the existing state-of-the-art baselines

Visual exploration of sparse traffic trajectory data

In this paper, we present a visual analysis system to explore sparse traffic trajectory data recorded by transportation cells. Such data contains the movements of nearly all moving vehicles on the major roads of a city. Therefore it is very suitable for macro-traffic analysis. However, the vehicle movements are recorded only when they pass through the cells. The exact tracks between two consecutive cells are unknown. To deal with such uncertainties, we first design a local animation, showing the vehicle movements only in the vicinity of cells. Besides, we ignore the micro-behaviors of individual vehicles, and focus on the macro-traffic patterns. We apply existing trajectory aggregation techniques to the dataset, studying cell status pattern and inter-cell flow pattern. Beyond that, we propose to study the correlation between these two patterns with dynamic graph visualization techniques. It allows us to check how traffic congestion on one cell is correlated with traffic flows on neighbouring links, and with route selection in its neighbourhood. Case studies show the effectiveness of our system

UHPLC-HRMSn Analysis Reveals the Dynamic Metabonomic Responses of Salvia miltiorrhiza Hairy Roots to Polysaccharide Fraction from Trichoderma atroviride

We have previously reported that Trichoderma atroviride, an endophytic fungus isolated from S. miltiorrhiza, promotes S. miltiorrhiza hairy root growth and significantly stimulates the biosynthesis of tanshinones specifically the polysaccharide fraction (PSF). However, this study only focused exclusively on six metabolites whilst ignoring changes to the whole metabolite composition of the S. miltiorrhiza hairy roots. In the present study, the dynamic metabonomic responses of S. miltiorrhiza hairy roots were investigated using ultra-high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMSn). UHPLC-HRMS typical total ions chromatograms (TICs) of PSF-treated hairy root samples were different from the control. Moreover, the results of principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and hierarchical clustering analysis (HCA) indicated that PSF-treated samples were significantly different from the control. Through the analysis of PLS-DA, a total of 114 and 99 differential metabolites were found from the positive and negative models respectively and a total of 33 differential metabolites were identified. Thus, S. miltiorrhiza hairy roots had been induced to regulate the metabolic profiling in response to PSF and the changes of the metabolic profiling contributed to promoting the biosynthesis of tanshinones notably whilst the biosynthesis of phenolic acids were slightly inhibited